Machine Learning Engineer
SweedSalary not specified
Full Time
Mid-level (3 to 4 years)
Not SpecifiedCompensation
N/AExperience Level
N/AJob Type
Not SpecifiedVisa
N/AIndustries
Requirements
- Advanced proficiency in Python
- 5+ years of experience in applied ML, large-scale distributed systems, or post-training infrastructure (RLHF, DPO, constitutional AI, etc.)
- Strong expertise with PyTorch and modern ML training frameworks; familiarity with distributed training and inference optimization
- Proven experience designing and operating data pipelines, benchmark frameworks, or large-scale evaluation systems
- Ability to drive technical projects end-to-end: from architecture design to implementation, scaling, and monitoring
- Clear and confident communication skills; ability to collaborate across research and engineering disciplines and influence technical direction
Responsibilities
- Architect, implement, and optimize large-scale post-training systems and data processing pipelines, ensuring reliability, scalability, and performance
- Lead the development of next-generation LLM benchmarks and evaluation frameworks, defining standards for measuring advanced reasoning, alignment, and knowledge capabilities
- Design and enforce rigorous methodologies for verifying data integrity and quality across highly specialized datasets
- Drive software/hardware performance optimization to accelerate experimentation and deployment (e.g., memory usage, training throughput, distributed systems)
- Partner with cross-disciplinary teams—including research scientists, domain experts, and product engineers—to validate and productionize model improvements
- Mentor junior engineers and shape technical best practices for the post-training and evaluation engineering pod
- Influence long-term research engineering strategy by identifying opportunities to systematize evaluation and data quality at scale
Skills
Handshake
Connects students with job opportunities
About Handshake
Handshake connects college students with job and internship opportunities through its platform. It serves over 15 million students, 1,500 universities, and 900,000 employers, focusing on early career recruitment. The platform allows universities to provide students access to job listings, career fairs, and recruitment events, while employers can post job openings and manage recruitment processes. Handshake's user-friendly interface helps students organize their job search and offers insights like company reviews. The company prioritizes data privacy and security, ensuring compliance with regulations like FERPA. Handshake aims to bridge the gap between students and employers, facilitating early career opportunities.
San Francisco, CaliforniaHeadquarters
2014Year Founded
$422.2MTotal Funding
SERIES_FCompany Stage
Cybersecurity, EducationIndustries
501-1,000Employees
Benefits
💰Equity and ownership in a fast-growing company.
🍼16 Weeks of paid parental leave
💝Comprehensive medical, dental, and vision
💻Handshake offers $500/£360 home office stipend
📚Generous learning & development opportunities and an annual $2,000/£1,500/2k€ stipend
🏦401k Match: Handshake offers a dollar-for-dollar match on 1% of deferred salary, up to a maximum of $1,200 per year.
🏝PTO
Risks
Emerging competitors like Fizz target Handshake's demographic with financial products.
Intuit's collaboration may draw students away from Handshake.
AI-driven skills demand may reduce engagement with Handshake.
Differentiation
Handshake connects over 15 million students with 900,000 employers.
The platform offers a user-friendly interface for job and internship applications.
Handshake ensures data privacy, complying with regulations like FERPA.
Upsides
Handshake's new social media-like interface boosts user engagement.
Growing student loan repayment benefits attract more employers to Handshake.
Demand for skills-based workforce aligns with Handshake's mission.
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